Motion assisted data enhancement

ABSTRACT

Embodiments related to enhancing data are disclosed.

FIELD

This application pertains to the field of imaging, and moreparticularly, to the field of motion assisted enhancement of data, whichmay include images, video and/or audio data, other data, and/orcombinations thereof.

BACKGROUND

Digital video and audio services such as transmitting digital images,video and/or audio information over wireless transmission networks,digital satellite services, streaming video and/or audio over theInternet, delivering video content to personal digital assistants orcellular phones, etc., are increasing in popularity. Interference maydegrade the data and/or image in measurement, processing ortransmission. Therefore, methods of correcting data and improving dataquality may be becoming more important.

DESCRIPTION OF THE DRAWINGS

The claimed subject matter will be understood more fully from thedetailed description given below and from the accompanying drawings ofembodiments, which should not be taken to limit the claimed subjectmatter to the specific embodiments described, but are for explanationand understanding only.

FIG. 1 is a diagram depicting an example enhancement of an image,according to an embodiment.

FIG. 2 is a diagram depicting pixel values within adjacent frames,according to an embodiment.

FIG. 3 is a diagram depicting a histogram of pixel values, according toan embodiment.

FIG. 4 is a flow diagram of one embodiment of a method for enhancingdata, according to an embodiment.

FIG. 5 is a block diagram of a computing platform capable of executingfeedback for out of range signals in accordance with one or moreembodiments.

It will be appreciated that for simplicity and/or clarity ofillustration, elements illustrated in the figures have not necessarilybeen drawn to scale. For example, the dimensions of some of the elementsmay be exaggerated relative to other elements for clarity. Further, ifconsidered appropriate, reference numerals have been repeated among thefigures to indicate corresponding and/or analogous elements.

DETAILED DESCRIPTION

In the following detailed description, numerous specific details are setforth to provide a thorough understanding of claimed subject matter.However, it will be understood by those skilled in the art that claimedsubject matter may be practiced without these specific details. In otherinstances, well-known methods, procedures, components and/or circuitshave not been described in detail.

An improved estimate of a noisy waveform represented by digitized datamay be obtained by processing. This processing may include, but is notlimited to, averaging of more than one data value, coherent averaging,and/or other processing, and/or combinations thereof. This processingmay be utilized if the data occurs repeatedly, if the instances of thewaveform can be aligned, and/or if the noise is additive. The noisepower may typically be reduced by half by averaging two instances of thedata, among other processing techniques.

Where the noise is not additive, other non-linear techniques may beutilized. These techniques may include, but are not limited to, removalof samples that may be outside of a range, and/or have values that maybe inconsistent with the other values being used.

A video sequence may include a series of frames of the same scene.Objects within that scene may change relatively slowly from frame toframe. If the data contains noise, but the objects are relatively staticfrom frame to frame, a better estimate of the data may be obtained byaveraging and/or other processing of the data values over a number offrames. Noise may be added via environmental conditions, as well as bythe recording, editing, processing data transmission, and/or receivingequipment. Therefore, estimating the value of the data may beaccomplished by processing multiple instances of a particular datavalue, from multiple frames.

In a sequence of frames, objects may tend to move within the scene. Aparticular pixel or group of pixels may be followed from frame to frame.Motion estimation techniques may be utilized to trace the pixel or groupof pixels from frame to frame. A trace, which may include a list ofpixel values, may be constructed based at least in part upon the motionestimation of the pixel or group of pixels from frame to frame. Thistrace of values may be processed to create an estimation of data valueswithin a frame and/or frames.

Objects may be represented by groups of pixel in a video sequence. Insome systems, irregularly shaped groups may be formed into video objectswhose motion may be described by a single vector. Another type of motionestimation may be optical flow, which may describe the motion of everypixel in an image by either a discrete vector for each pixel, and/or bya mathematical description of the motion. Other techniques may beutilized to achieve smoothness of the objects from frame to frame.Combinations of all of these techniques may be utilized to enhance thedata.

A pixel or group of pixels may be identified in a frame of interest, ortarget frame. The position of the pixel or group of pixels may then beidentified in the frames adjacent to the target frame. The values of thepixel or group of pixels may then be processed to estimate the value ofthe pixel or group of pixels in the target frame, as well as otherframes. Pixels adjacent to the pixel or group of pixels may also beutilized to enhance the data. The processing may be combinations of theabove-described process to enhance the data. If the motion is at thesub-pixel level, the trace may be constructed by interpolating fromadjacent pixels.

One consideration may be the number of frames to be utilized. Betternoise reduction may be achieved with the use of more data. However, ifthe pixel or group of pixels drift into other objects, and/or a suddenchange of illumination occurs, the trace may be terminated because thevalues may not be representative of the data to be enhanced. Therefore,it may be advantageous to examine the data before, during, and/or afterthe trace is constructed in the estimation process to further enhancethe data.

Furthermore, once a trace has been constructed, a determination may bemade to use, or not to use certain values. The values may be excluded ifthey fall outside a range. The range may be predetermined and/ordetermined after the values are present in the trace. A histogram ofvalues may be constructed to better analyze the data. If the data in thehistogram had one peak, and/or was reasonably symmetric, then it may berelatively likely that either a mean or median of the histogram may be arelatively attractive estimate of the pixel or group of pixels value.This estimation may further depend on whether the noise is purelyadditive, and to what degree obscuritive noise is present.

When evaluating the trace and/or histogram, some values may be far fromthe mean and/or median. These values may be excluded as obscuritive.This may occur as a result of a few bright values, such as “shot noise”and may adversely affect the estimation of the data. It may also bepossible that too many frames may have been utilized in creating thetrace and/or histogram or by processing of the trace to detect a trend.This may be determined by examining the standard deviation of the traceand/or histogram. A different length of trace may occur for differentpixels or group of pixels within the same image. For this reason, tracesmay be saved for use by other traces to better estimate the data.

This process may be utilized for an entire video sequence, or for aportion of a video sequence. Furthermore, traces may be utilized toenhance data from more than one frame. Because spatial and/or temporalconsistencies may exist in frames of video, constructing a trace mayinclude linear and/or nonlinear spatial filtering, may be used in thetrace and/or may be applied after the trace is constructed. Furthermore,the above-described techniques may be utilized with other methods ofvideo enhancement to further enhance the data.

FIG. 1 is a diagram of one embodiment of a sequence of frames used formotion assisted data enhancement, at 100. In an embodiment, frames 100may be consecutive frames of a motion image. An embodiment may include atarget frame 120, as well as frames in a positive 124, and negative 122directions, with relation to target frame 120. The positive and negativedirections may indicate a frame in time, however, the scope of thisdisclosure is not limited in this respect. Target frame 120 may includea data point and/or pixel 102. In the embodiment of motion image, datapoint and/or pixel 102 may be followed and/or traced between the targetframe 120 and one or more adjacent frames, 122, 124. The data pointand/or pixel position in adjacent frames 122 may correspond to pixels atpositions 104, 106 and 108, respectively. Similarly, data point and/orpixel positions 110, 112, and 114 may correspond to adjacent frames 124.

A trace 116 may be created from the pixel positions in adjacent framesof a data point and/or pixel 102. The trace may utilize vectors, such asat 140, 142, and 144, at least in part, to determine data point and/orpixel locations 110, 112, and 114, respectively. However, many othermethods and systems may be utilized to create trace 116, and the scopeof this disclosure is not limited in this respect. Similarly, vectors134, 136, and 138 may be utilized, at least in part, to form anotherportion of trace 116.

The particular image values may be obtained from the data point and/orpixels at the locations, once the locations are known. The image valuesmay indicate color, intensity, and/or many other properties, and/orcombinations thereof. These values may be utilized to estimate a valueat data point and/or pixel 102 that may be closer to the original valueand/or intended value. The value at data point and/or pixel 102 may havebeen distorted by noise, interference in the transmission, and/orcreated by devices handling the data. Seven frames have been shown hereto better understand the subject matter. However, the scope of theclaimed subject matter is not limited in this respect.

These values may be utilized to form a histogram 200, as shown in FIG.2. FIG. 2 may be an embodiment of a graph and/or histogram of values 210from pixel 102 from the target frame 120 and one or more adjacentframes. The values may be used to estimate a value at data point and/orpixel 102. In an embodiment, the values may be averaged, filtered, amedian, mode, and/or means may be found. Combinations of these differentcalculations may be utilized to better determine the original and/orintended value of data point and/or pixel 102. It will be understoodthat many different calculations and/or processing of these values maybe accomplished without straying from the concepts disclosed here, andthis disclosure is not limited in this respect.

FIG. 3 may show a histogram 300, according to an embodiment. Histogram300 may include values 310. Histogram 300 may also include a determinedrange 320. Values within the determined range 320 may be utilized incalculation for an estimation of the value at the data point. Histogram300 may also include values 330 outside of determined range 320. Thesevalues may not be utilized in calculation of the estimation of thevalues at a data point. The use of many values to estimate a value for apixel may allow the non-use of pixel values, which are abhorrent, orcorrupted. In this manner, a better estimation of a pixel value may beobtained.

Determined range 320 may be predetermined by a user and/or applicationprogram, in an embodiment, but may be predetermined in many other ways.Furthermore, the range may be determined upon the values collected forthe trace. In an embodiment, values within a determined range from amean, median, and/or mode, and/or combinations thereof may be utilized.However, it will be appreciated that many other methods and systems fordetermining determined range 320 may be utilized without straying fromthe spirit and scope of this disclosure. The data in the histogram maybe filtered to filter out noise or corrupted data. Furthermore,filtering may occur before the data is placed into the histogram.

FIG. 4 is a flow diagram illustrating a method according to anembodiment, at 400. Method 400 may include determining and/or receivingvectors at 410. Vectors may be determined in many ways including, butnot limited to, optical flow and/or block matching, and/or combinationsthereof. Furthermore, vectors may be precalculated, or the vectors maybe received and utilized.

Method 400 may further include creating a trace 412. Once the positionof a pixel in adjacent frames is determined, one or more pixel valuesmay be utilized to form a trace. The trace may be created using pixelvalues from adjacent frames, as well as other frames, as desired. Thetrace may be utilized to create a histogram, upon which manycalculations may be performed to estimate a pixel value at 414.

Estimating a pixel value 414 may include creating a histogram andperforming many different calculations upon the values in the histogram.Estimating may also include excluding values from utilization from usein the calculation. The estimation may be based at least in part upon,but not limited to, the average, the median, the mode, the mean, and/orcombinations thereof. Furthermore, the estimation may take into accountother pixel traces, and may be utilized for more than one pixel in morethan one frame and/or trace.

The pixel trace may be terminated at 416. The determination to terminatethe trace may be based upon a certain number of frames utilized, as wellas the values found within a frame. If the values within the frame arefound to be outside a range, the values may not be suitable for use andthe trace may be terminated. It will be appreciated that many otherevents and/or determinations may be utilized to terminate the trace. Themethod then continues at 420.

Referring now to FIG. 5, a block diagram of a computing platform capableof enhancing data in accordance with one or more embodiments will bediscussed. It should be noted that computing platform 500 of FIG. 5 ismerely one type of computing platform, and other computing platformshaving more and/or fewer and/or different components than shown in FIG.5 may be implemented, and the scope of claimed subject matter is notlimited in this respect. In one or more embodiments, computing platform500 may be utilized to implement process 400 in whole and/or using moreand/or fewer blocks than shown in FIG. 4, and the scope of claimedsubject matter is not limited in this respect. Computing platform 500may include processor 510 coupled to cache random access memory (RAM)512 via back side bus 511. Processor 510 may also couple to a chipsetthat includes Northbridge chip 516 via front side bus 514, and also toSouthbridge chip 518 via bus 520. In one embodiment, Northbridge chip516 in general may be utilized to connect a processor to memory, to aninput/output bus, to a video bus, and to Level 2 cache, although thescope of claimed subject matter is not limited in this respect.

In one embodiment, Southbridge chip 518 may be utilized to controlinput/output functions, the basic input/out system (BIOS), and interruptcontrol functions of Integrated Drive Electronics (IDE) devices, such ashard disks or compact disk read-only memory (CD-ROM) devices or thelike, although the scope of claimed subject matter is not limited inthis respect. Random access memory (RAM) 522 may couple to Northbridgechip 516 via main memory bus 524, and input/output (I/O) controller 526may also couple to Northbridge chip 516 via I/O bus 528. In oneembodiment, 1/0 controller 526 and I/O bus 528 may be in compliance witha Small Computer Systems Interface (SCSI) specification such as theAmerican National Standards Institute (ANSI) X3.131-1994 SCSI-2specification, although the scope of claimed subject matter is notlimited in this respect. In an alternative embodiment, I/O controller526 and I/O bus 528 may be in compliance with a Peripheral ComponentInterconnect (PCI) bus, although the scope of claimed subject matter isnot limited in this respect.

Video controller 530 may couple to Northbridge chip 516 via video bus532, which in one embodiment may comprise an Accelerated Graphics Port(AGP) bus, although the scope of claimed subject matter is not limitedin this respect. Video controller 530 may provide video signals to anoptionally coupled display 534 via display interface 536, which in oneembodiment may comprise a Digital Visual Interface (DVI) in compliancewith a standard promulgated by the Digital Display Working Group,although the scope of claimed subject matter is not limited in thisrespect. Southbridge chip 518 may couple to a peripheral componentinterconnect to peripheral component interconnect (PCI-PCI) bridge 538via input/output bus 540, which may in turn couple to I/O controller 542to control various peripheral devices such as Universal Serial Bus (USB)devices, or devices compatible with an Institute of Electrical andElectronics Engineers (IEEE) 1394 specification, although the scope ofclaimed subject matter is not limited in this respect.

For example, some portions of the detailed description are presented interms of processes, programs and/or symbolic representations ofoperations on data bits and/or binary digital signals within a computermemory. These processes, descriptions and/or representations may includetechniques used in the data processing arts to convey the arrangement ofa computer system and/or other information handling system to operateaccording to such programs, processes, and/or symbolic representationsof operations.

A process may be generally considered to be a self-consistent sequenceof acts and/or operations leading to a desired result. These includephysical manipulations of physical quantities. Usually, though notnecessarily, these quantities take the form of electrical and/ormagnetic signals capable of being stored, transferred, combined,compared, and/or otherwise manipulated. It may be convenient at times,principally for reasons of common usage, to refer to these signals asbits, values, elements, symbols, characters, terms, numbers and/or thelike. However, these and/or similar terms may be associated with theappropriate physical quantities, and are merely convenient labelsapplied to these quantities.

Unless specifically stated otherwise, as apparent from the followingdiscussions, throughout the specification discussion utilizing termssuch as processing, computing, calculating, determining, and/or thelike, refer to the action and/or processes of a computing platform suchas computer and/or computing system, and/or similar electronic computingdevice, that manipulate and/or transform data represented as physical,such as electronic, quantities within the registers and/or memories ofthe computer and/or computing system and/or similar electronic and/orcomputing device into other data similarly represented as physicalquantities within the memories, registers and/or other such informationstorage, transmission and/or display devices of the computing systemand/or other information handling system.

Embodiments claimed may include one or more apparatuses for performingthe operations herein. Such an apparatus may be specially constructedfor the desired purposes, or it may comprise a general purpose computingdevice selectively activated and/or reconfigured by a program stored inthe device. Such a program may be stored on a storage medium, such as,but not limited to, any type of disk including floppy disks, opticaldisks, CD-ROMs, magnetic-optical disks, read-only memories (ROMs),random access memories (RAMs), electrically programmable read-onlymemories (EPROMs), electrically erasable and/or programmable read onlymemories (EEPROMs), flash memory, magnetic and/or optical cards, and/orany other type of media suitable for storing electronic instructions,and/or capable of being coupled to a system bus for a computing device,computing platform, and/or other information handling system. However,the computer program product may also be capable of being downloadeddirectly to the computing device, such as, but not limited to, adownload over the Internet and/or other network and/or communication.This disclosure is intended to encompass a carrier wave format.

The processes and/or displays presented herein are not necessarilylimited to any particular computing device and/or other apparatus.Various general purpose systems may be used with programs in accordancewith the teachings herein, or a more specialized apparatus may beconstructed to perform the desired method. The desired structure for avariety of these systems will appear from the description below. Inaddition, embodiments are not described with reference to any particularprogramming language. It will be appreciated that a variety ofprogramming languages may be used to implement the teachings describedherein.

In the description and/or claims, the terms coupled and/or connected,along with their derivatives, may be used. In particular embodiments,connected may be used to indicate that two or more elements are indirect physical and/or electrical contact with each other. Coupled maymean that two or more elements are in direct physical and/or electricalcontact. However, coupled may also mean that two or more elements maynot be in direct contact with each other, but yet may still cooperateand/or interact with each other. Furthermore, the term “and/or” may mean“and”, it may mean “or”, it may mean “exclusive-or”, it may mean “one”,it may mean “some, but not all”, it may mean “neither”, and/or it maymean “both”, although the scope of claimed subject matter is not limitedin this respect.

Reference in the specification to “an embodiment,” “one embodiment,”“some embodiments,” or “other embodiments” means that a particularfeature, structure, or characteristic described in connection with theembodiments is included in at least some embodiments, but notnecessarily all embodiments. The various appearances of “an embodiment,”“one embodiment,” or “some embodiments” are not necessarily allreferring to the same embodiments.

In the foregoing specification, claimed subject matter has beendescribed with reference to specific example embodiments thereof. Itwill, however, be evident that various modifications and/or changes maybe made thereto without departing from the broader spirit and/or scopeof the subject matter as set forth in the appended claims. Thespecification and/or drawings are, accordingly, to be regarded in anillustrative rather than in a restrictive, sense.

1. A method, comprising: identifying one or more data points in a targetframe and corresponding one or more data points in at least one adjacentframe; creating a trace based at least in part upon the identified oneor more data points in a target frame and at least one adjacent frame;and estimating the value of the one or more data points in the targetframe based at least in part upon values of the data points in thetrace.
 2. The method according to claim 1, further comprisingdetermining motion vectors for one or more data points from a targetframe and adjacent frames, which the trace is based at least in partupon.
 3. The method according to claim 2, wherein the determining motionvectors comprises block matching of selected frames.
 4. The methodaccording to claim 2, wherein the determining motion vectors comprisesoptical flow of selected frames.
 5. The method according to claim 1,further comprising receiving motion vectors for one or more data pointsfrom a target frame and adjacent frames, from which the trace is basedat least in part upon.
 6. The method according to claim 1, wherein saidestimated value of the one or more data points is utilized in at leastone frame other than the target frame.
 7. The method according to claim1, wherein the adjacent frames are adjacent in time.
 8. The methodaccording to claim 1, wherein the adjacent frames are more than oneframe apart in time.
 9. The method according to claim 1, wherein saidestimating comprises creating a histogram of values based at least inpart upon the data points utilized for the trace.
 10. The methodaccording to claim 9, wherein said estimating further comprisesperforming calculations utilizing the values of the histogram.
 11. Themethod according to claim 10, wherein said estimating further comprisesutilizing a value, based at least in part upon the determination thatthe value is within a determined range.
 12. The method according toclaim 11, wherein said estimating further comprises excluding a value,based at least in part upon the determination the value is outside adetermined range.
 13. The method according to claim 12, wherein thedetermined range is based at least in part upon a range of values of thedata point within a sequence of frames.
 14. The method according toclaim 12, wherein the determined range is based at least in part upon arange of values of the data points utilized in the histogram.
 15. Themethod according to claim 12, further comprising excluding all valuesfrom a frame, based at least in part upon a determination that adetermined number of values within a frame are outside a determinedrange.
 16. The method according to claim 12, further comprisingterminating the trace in a particular direction, based at least in partupon the determination that all values in a frame are outside adetermined range.
 17. The method according to claim 1, wherein saidestimating is based at least in part upon a temporal position of a framewith respect to the target frame.
 18. The method according to claim 12,wherein said estimating is based at least in part upon a value of a datapoint outside the determined range.
 19. The method according to claim 1,wherein said estimating is based at least in part upon a median of thevalues of the trace.
 20. The method according to claim 1, wherein saidestimating is based at least in part upon a mean of the values of thetrace.
 21. The method according to claim 1, wherein said estimating isbased at least in part upon a mode of the values of the trace.
 22. Themethod according to claim 1, wherein said estimating is based at leastin part upon an adjacent trace.
 23. The method according to claim 1,wherein creating a trace comprises filtering of potential data pointvalues.
 24. The method according to claim 1, wherein creating a tracecomprises utilizing sub-pixel accuracy.
 25. The method according toclaim 1, wherein said estimating comprises determining a value based atleast in part upon values adjacent the data point within a frame.
 26. Acomputer program product capable of being stored on a computer readablemedium comprising instructions that, if executed by a computingplatform, result in motion assisted enhancement of data, by: identifyingone or more data points in a target frame and corresponding data pointsin at least one adjacent frame; creating a trace based at least in partupon the identified one or more data points in a target frame and atleast one adjacent frame; and estimating the value of the one or moredata points in the target frame based at least in part upon values ofthe data points in the trace.
 27. The product according to claim 26,further comprising determining motion vectors for one or more datapoints from a target frame and adjacent frames, which the trace is basedat least in part upon.
 28. The product according to claim 27, whereinthe determining motion vectors comprises block matching of selectedframes.
 29. The product according to claim 27, wherein the determiningmotion vectors comprises optical flow of selected frames.
 30. Theproduct according to claim 26, further comprising receiving motionvectors for one or more data points from a target frame and adjacentframes, from which the trace is based at least in part upon.
 31. Theproduct according to claim 26, wherein said estimated value of the oneor more data points is utilized in one or more frames.
 32. The productaccording to claim 26, wherein said estimating comprises creating ahistogram of values based at least in part upon the data points utilizedfor the trace.
 33. The product according to claim 32, wherein saidestimating further comprises performing calculations utilizing thevalues of the histogram.
 34. The product according to claim 33, whereinsaid estimating further comprises utilizing a value, based at least inpart upon the determination that the value is within a determined range.35. The product according to claim 34, wherein said estimating furthercomprises excluding a value, based at least in part upon thedetermination the value is outside a determined range.
 36. The productaccording to claim 35, wherein the determined range is based at least inpart upon a range of values of the data point within a sequence offrames.
 37. The product according to claim 35, wherein the determinedrange is based at least in part upon a range of values of the datapoints within the histogram.
 38. The product according to claim 26,wherein said estimating is based at least in part upon an adjacenttrace.
 39. The product according to claim 26, wherein creating a tracecomprises filtering of potential data point values.
 40. The productaccording to claim 26, wherein the creating a trace comprises utilizingsub-pixel accuracy.
 41. The product according to claim 26, wherein saidestimating comprises determining a data point value based at least inpart upon data point values adjacent the data point within a frame. 42.A system for enhancing data, comprising: means for identifying one ormore data points in a target frame and corresponding data points in atleast one adjacent frame; means for creating a trace based at least inpart upon the identified one or more data points in a target frame andat least one adjacent frame; and means for estimating the value of theone or more data points in the target frame based at least in part uponvalues of the data points in the trace.
 43. The system according toclaim 42, further comprising means for determining motion vectors forone or more data points from a target frame and adjacent frames, whichthe trace is based at least in part upon.
 44. The system according toclaim 43, further comprising means for receiving motion vectors for oneor more data points from a target frame and adjacent frames, from whichthe trace is based at least in part upon.